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| Section | Objectives |
|---|---|
| Topic 1: Evaluation and Ethics | - Bias, safety, and responsible AI use - Evaluating AI output quality |
| Topic 2: Foundations of Artificial Intelligence | - Natural Language Processing overview - Basic AI concepts and terminology |
| Topic 3: Applied Prompt Design | - Domain-specific prompting scenarios - Task-specific prompt construction |
| Topic 4: Prompt Engineering Principles | - Prompt refinement and iteration techniques - Prompt structure (instructions, context, persona, output format) |
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NEW QUESTION # 13
What is an example of a prompt that has an appropriate level of specificity?
Answer: A
Explanation:
Specificity is the cornerstone of effective prompt engineering. A specific prompt provides clear boundaries and a narrow focus, which prevents the AI from generating generic or overwhelming amounts of irrelevant information. Option C, "Provide an overview of state representative election laws in Iowa," is the best example because it defines three critical parameters: theSubject(election laws), theScope(state representative level), and theLocation/Jurisdiction(Iowa).
In contrast, options A and D are far too broad; asking for an overview of four major sciences or all business regulations would result in a superficial summary that lacks depth. Option B is subjective and lacks context, as "best classes" depends entirely on the student's major and career goals. By specifying the state and the specific legislative body, the user in Option C allows the AI to access a targeted subset of its training data. In practical applications, this level of specificity significantly reduces the risk of "hallucinations" or factual errors, as the model is guided to a precise factual domain. This is essential in professional research where accuracy and relevance are prioritized over general knowledge.
NEW QUESTION # 14
Which task can be accomplished with the data cleaning capabilities of generative AI?
Answer: D
Explanation:
Generative AI models, specifically Large Language Models (LLMs), are highly effective atIdentifying inaccuracieswithin a dataset during the data cleaning phase. When provided with a dataset and a prompt to
"check for consistency" or "identify anomalies," the AI can cross-reference the data points against its internal knowledge base or the logical rules established in the prompt. For example, if a list of "US States" includes
"London," the AI can flag this as an inaccuracy.
This capability extends to identifying spelling errors, formatting inconsistencies (e.g., dates written in multiple formats), and logical contradictions. While AI can help in identifying bias (Option D), that is usually considered a higher-level "auditing" task rather than a standard "cleaning" task. Identifying inaccuracies is a foundational step in the data pipeline; by cleaning the data first, the user ensures that any subsequent analysis or "conclusion drawing" (Option C) is based on high-quality, reliable information. In prompt engineering, this is often performed using the "Self-Correction" or "Reviewer" pattern, where one prompt generates data and a second prompt is used specifically to identify and fix any factual or structural inaccuracies within that output.
NEW QUESTION # 15
What is an important component to include in an AI prompt used to generate an image?
Answer: D
Explanation:
In the context of text-to-image generative AI, theMain subjectis the most critical component of the prompt.
While technical parameters like resolution (Option A) or file size (Option D) can sometimes be adjusted via specific suffixes or settings, the AI cannot begin the diffusion process without a clear definition ofwhatit is supposed to visualize. The main subject acts as the "anchor" for the entire generation process, providing the primary semantic information that the model uses to map noise to a coherent image.
An effective image prompt typically starts with the subject (e.g., "a golden retriever"), followed by descriptive modifiers (e.g., "wearing a space suit"), and finally, stylistic or environmental details (e.g., "cinematic lighting, 8k, digital art style"). If the main subject is vague or missing, the AI may produce a generic landscape or a chaotic abstract image. In professional design workflows, identifying the subject clearly ensures that the AI's creative "energy" is focused on the correct focal point. This allows the user to later refine the "medium" or "mood" of the image without changing the core content. Without a well-defined subject, the rest of the prompt's descriptors have no context to adhere to, leading to unpredictable and often unusable results.
NEW QUESTION # 16
Which generative AI tool allows users to create engaging and dynamic content with templates and stock footage?
Answer: B
Explanation:
Invideois a generative AI platform specifically designed for video creation. It distinguishes itself from text-to- image or text-to-text models by providing a comprehensive suite of tools that combine AI-generated scripts with a library of stock footage, music, and templates. Users can provide a single text prompt describing a video concept, and the AI will generate a script, select relevant video clips, and even provide a voiceover.
This tool is a prime example of an "application-specific" generative medium. While ChatGPT can write the script and Midjourney can create the thumbnails, Invideo integrates these capabilities into a single workflow for content creators and marketers. The "prompting" in Invideo is often more about "Art Direction" than linguistic structure; users must specify the target platform (e.g., "YouTube Shorts"), the target audience, and the desired aesthetic. Evaluating this medium involves understanding how AI interacts with pre-existing assets (stock footage) versus creating entirely new ones from scratch. It represents the shift from "Generative AI" as a novelty to "Generative AI" as a functional production tool.
NEW QUESTION # 17
Which content creation tool specializes in versatile image creation through detailed text prompts?
Answer: C
Explanation:
Midjourneyis a generative AI tool that specifically specializes in high-quality, versatile image creation through sophisticated text prompts. While other tools like DALL-E are integrated into larger ecosystems (like OpenAI's ChatGPT), Midjourney has gained a reputation for its distinct artistic style, high resolution, and deep "parameter" controls that allow prompt engineers to fine-tune lighting, camera angles, and textures.
Midjourney operates primarily through a Discord interface, where users utilize "slash commands" (like
/imagine) to initiate generations. It is favored by designers and concept artists because of its ability to interpret complex, evocative language into visually stunning outputs. Unlike ChatGPT, which is primarily a text-based LLM, Midjourney is a "Diffusion Model" specifically trained on image-caption pairs. Evaluating Midjourney as a medium requires understanding that the "syntax" of the prompt differs from text models; it relies heavily on artistic descriptors, style references (e.g., "unreal engine," "octane render"), and aspect ratio constraints to achieve the desired outcome.
NEW QUESTION # 18
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